tbuckley/cabot-search huggingface dataset:
Clinical experience with rucaparib after prior PARPi treatment: A subanalysis from the rucaparib access program in Spain by GEICO.
Authors: Alfonso Yubero-Esteban, Piedad Reche-Molina, Carmen Salvador Coloma, Purificación Estévez-García, Luis Manso, Marcos Iglesias Campos, Arantzazu Barquin, Raul Marquez, Ana Santaballa, Julia Calzas, Ana Herrero, Victoria Casado, Julia Madani, Maria Merino, Gloria Marquina, Jesus Alarcon Company, Lydia Gaba, Jose Fuentes Pradera, Antonio Gonzalez Martin, Maria Luisa Sanchez Lorenzo
Journal: Journal of Clinical Oncology (2022)

e17598 Background: Rucaparib is a PARP inhibitor (PARPi) approved as maintenance therapy for platinum (Pt)-sensitive recurrent high-grade ovarian cancer (HGOC), and as treatment for BRCA-mutant HGOC patients. To date, there is little evidence about the efficacy and safety of rucaparib after prior exposure to PARPi. This subanalysis aims to describe the patients’ characteristics and treatment outcomes with rucaparib in women who were included in the rucaparib early access program (RAP) in Spain and had received a prior PARPi. Methods: A retrospective study was conducted by GEICO at 22 hospitals in Spain to analyze data of 51 women treated within the RAP (600 mg BID). Adult women with HGOC, fallopian tube, or primary peritoneal cancer, who had received at least one prior PARPi before rucaparib were analyzed. Patients’ characteristics, medical history, safety, efficacy, and dosing data were collected. Results: A total of 14 women, with a median age of 63 years old (42-78) were included in this subanalysis. Of them, 92.9% were diagnosed of epithelial ovarian cancer and 78.6% had mutations in BRCA1/ 2 genes. The median number of lines before rucaparib was 5 (3-8), while the number of lines before the first PARPi was 3 (2-5). Except for one woman who had received 2 prior PARPis before rucaparib, the others had received just 1. Most patients were given olaparib as the first PARPi (n = 12, 85.8%), while niraparib was the initial PARPi in the remaining cases (n = 2, 14.3%). The outcomes of the treatment with rucaparib in these patients are outlined in table 1. Rucaparib was given as maintenance therapy in 1 patient and as treatment in 13 patients, 12 of them being Pt-resistant. The progression-free survival (PFS) ranged from 0.23 to 9.12 months. Adverse events (AE) of any grade were detected in 78.6% of patients, whereas AE of grade ≥3 affected 28.6% of women. Rucaparib dose was interrupted in 57.1% and reduced in 42.9% of patients. Only 1 patient discontinued rucaparib due to toxicity. No new safety signals were detected. Conclusions: This is one of the first real-word studies reporting the use of rucaparib after treatment with another PARPi. Even in these heavily pre-treated patients who had received prior PARPi, rucaparib efficacy has been notable in some cases, and its safety profile is consistent with that reported in previous clinical trials. Future studies should focus on the selection of patients who could benefit from rucaparib after prior PARPi exposure. [Table: see text]
A quantitative analysis of escalating antineoplastic medication price increases.
Authors: Michail Alevizakos, Bruno Bockorny
Journal: Journal of Clinical Oncology (2022)

6592 Background: Established antineoplastic medication prices are overall increasing, yet the yearly trend and additive cost of such increases relative to overall antineoplastic spending is often unclear. Methods: We accessed the yearly reimbursement files from Medicare Part B for parenteral antineoplastic agents (codes J8501-J9999) for the years 2010-2020 and adjusted all values to 2020 USD to account for inflation. We calculated an initial inflation-adjusted price-per-claim for every medication at the time of medication entry to the database and compared that price with the yearly price-per-claim that Medicare reimbursed. For medications whose price had increased beyond the initial inflation-adjusted price, we multiplied the annual differences with the total annual claims of the medication reimbursed in order to calculate the additional cost accrued by Medicare for every affected year. We only included medications with total annual cost &gt;10 million USD/yr in our analysis. Results: Price increases were noted in 70.9% of already established medications annually (median 74.5%, range 52.17-81.48%). This led to an average additional extra cost of 311 million USD (range 156-492 million USD) annually, for a total of 3.1 billion USD over the 10 years of observation. This extra cost represented 4.6-9.3% of the total Medicare Part B spending for antineoplastic medications annually and this percentage rose yearly by a statistically significant 0.43% (95% CI 0.14%-0.73%, P = 0.01; R 2 0.59) in absolute terms (Table). Rituximab (1,003 million USD), trastuzumab (421 million USD), and bevacizumab (326 million USD) accumulated the highest extra costs. Conclusions: The majority of established parenteral antineoplastics are affected by escalating price increases beyond the rate of inflation. Year-by-year, these increases occupy a progressively larger part of overall Medicare Part B spending. Since Medicare does not negotiate medication price nor receives rebates but rather relies on average market prices, these increases likely affect other U.S. markets as well.[Table: see text]
Clinical and laboratory parameters associated with rapid progression in advanced NSCLC patients treated with second or third-line single agent immune checkpoint inhibitors (ICIs).
Authors: Megan Randall, Philip D. Bonomi, Sanjib Basu, Jeffrey Allen Borgia, Hita Moudgalya, Revathi Kollipara, Marta Batus, Mary Jo J. Fidler
Journal: Journal of Clinical Oncology (2022)

e21087 Background: While laboratory parameters including PDL1 expression and NLR are associated with outcomes in patients with metastatic NSCLC treated with ICIs, these measures have not identified patients with rapid progression (RP) defined as progressive disease within 30 days. Clinical factors including patient age and weight loss have been associated with cancer outcomes in general. Identifying clinical correlates for NSCLC patients who experience RP on ICI therapy would be useful. Methods: The objective of this retrospective study was to evaluate relationships between pre-treatment cachexia and inflammation and RP in NSCLC patients who received 2nd- or 3rd- line single agent ICIs. Associations of age, race, gender, smoking status, and longitudinal changes in weight and NLR (from at least 6 weeks prior to treatment initiation) with RP were analyzed by univariate and multivariate statistical (Kaplan-Meier and related) methods. Results: 195 patients were included: 59% female, 18% Black, and 78% current or former smokers. 14% of patients had RP. Black race was associated with RP (HR = 2.32, p = 0.03). 191 patients had pretreatment weight available. 63% had weight loss prior to ICI, 25% with &gt; 5% loss. Any weight loss and weight loss &gt; 5% over the time period ≥6 weeks prior to treatment initiation were associated with RP (HR = 3.19 and 6.40, p = 0.03 and &lt; 0.01). 188 patients had pretreatment NLR values, 63% and 42% had NLRs &gt; 3.5 and &gt; 5, respectively. Pre-treatment NLR &gt; 5 and higher baseline NLR were associated with increased risk of RP (p = 0.03 and p &lt; 0.01). In multivariate analysis adjusted by age, smoking status and weight change, higher pre-treatment NLR is found to differentially increase RP risk for black patients (interaction HR = 1.27, p = 0.03). A model with these 5 variables provided 84.5% AUC of ROC curve (80% sensitivity, 75% sensitivity) for prognosticating RP. Conclusions: This retrospective study identified clinical variables including pre-treatment NLR &gt; 5, weight loss &gt; 0% &amp; &gt; 5%, black race, smoking status, and age that were associated with RP in previously treated advanced NSCLC patients receiving single agent ICIs. Though this requires validation with racially diverse data sets, these clinical parameters may be useful in identifying patients at high risk of RP on 2 nd or 3 rd line ICI therapy. Future directions include evaluating clinical characteristics and laboratory parameters in NSCLC patients treated with ICIs combined with chemotherapy and novel immunotherapy regimens, as well as single agent ICIs in the first line setting. If these clinical characteristics are associated with frequent RP in the setting of first line ICI treatment, it would be reasonable to consider novel immune strategies in this patient subset.
A phase II clinical trial of camrelizumab (CAM, an IgG4 antibody against PD-1) combined with apatinib (APA, a VEGFR-2 tyrosine kinase inhibitor) and temozolomide (TMZ) as the first-line treatment for patients (pts) with advanced acral melanoma (AM).
Authors: Lu Si, Caili Li, Xue Bai, Li Zhou, Lili Mao, Chuanliang Cui, Zhihong Chi, Xinan Sheng, Bin Lian, Xuan Wang, Bixia Tang, Xieqiao Yan, Siming Li, Yan Kong, Jie Dai, Xiaoting Wei, Juan Li, Fan Yang, Zheng Pang, Jun Guo
Journal: Journal of Clinical Oncology (2022)

9508 Background: PD-1 monotherapy as the first line stand treatment for advanced melanoma yields an objective response rate (ORR) of &lt; 20% in AM. Although multiple clinical trials are ongoing testing TMZ/APA, TMZ/PD-1 and APA/PD-1 combo therapies in AM, the reported ORR (range 17-23.8%) are far from satisfactory. We therefore conducted a phase II study of CAM/APA/TMZ combo in this subtype aiming for improved efficacy. Methods: We performed a single center, single arm phase II study (NCT04397770) testing the efficacy and safety of CAM/APA/TMZ combo as first-line therapy in pts with advanced AM. The primary endpoint was ORR per RECIST1.1, secondary endpoints included progression free survival (PFS), disease control rate (DCR), overall survival (OS), and safety. All pts received iv CAM (200mg q2w), iv TMZ (200mg/m2 d1-5, q4w) and po APA (250mg qd) until disease progression or intolerable toxicity. Results: By Jan 2022, fifty pts were enrolled (48 evaluable), the median follow-up was 12.1 mo (IQR 8.4-14.5). Thirty-one pts achieved CR/PR as the best response (including 1 CR and 30 PR), the ORR was 64.6% (95% CI 49.4-77.4%). The DCR was 95.8% (95%CI, 84.6-99.3%). Both the median PFS and OS was not reached (NR); 6-mo and 12-mo PFS rate was 81.7% (95%CI 71.6-93.3%) and 62.9% (95%CI 48.4-81.7%), respectively; 12-mo OS rate was 82.3% (95%CI 68.2-99.2%). The incidence of treatment-related adverse events (TRAEs) was 94% (47/50). Of 50 patients, the most common grade ≥3 TRAEs included γ-glutamyl transferase elevation (24.0%), direct bilirubin elevation (22.0%), aspartase transaminase elevation (20.0%), alanine transaminase elevation (16.0%), and hypertriglyceridemia (14.0%). No treatment-related deaths occurred. Conclusions: The CAM/APA/TMZ combination demonstrated promising efficacy as the first-line treatment for pts with advanced AM, and was generally well tolerated. Phase III randomized control trial is warranted. Clinical trial information: NCT04397770.
Associations between cancer history, social distancing behaviors, and loneliness in adults during the COVID-19 pandemic.
Authors: Jenny Yang, Xiaochen Zhang, Ivy Yu, James L. Fisher, Cecilia DeGraffinreid, Electra D. Paskett
Journal: Journal of Clinical Oncology (2022)

e24124 Background: Due to COVID-19, social distancing initiatives have been enacted, highlighting differences of social distancing practices and the resulting loneliness in various populations, especially in those with a history of cancer (survivors and those in active treatment). The objective of this study was to examine whether social distancing practices and loneliness differ between individuals with and without a history of cancer during the COVID-19 pandemic. Methods: This study is part of the “Impact of COVID-19 on Behaviors across the Cancer Control Continuum in Ohio” project conducted from June to November 2020. Participants from previous studies (N = 32,989) who had given permission to be re-contacted were invited to complete a survey online, by phone, or by mail. For the current analysis, participants who had complete data on history of cancer diagnosis, COVID social distancing behaviors (staying at home, not having visitors, staying 6 feet apart, wearing a masking indoors, and wearing a mask outdoors), attendance at social gatherings, contact with people outside of their household, and feelings of loneliness were included. Linear and logistic regression models were used to determine the associations between demographics, cancer history, social distancing, and loneliness. Results: Among the eligible participants (n = 5729), 54.9% had a cancer history (n = 3147), while 45.1% did not have a cancer history (n = 2582). The average age was 56.7 years, 35.6% were male, 89.4% were White, 74.7% were partnered, and 74.5% lived in metro counties. Out of all individuals, 69.3% participated in ≥4 of the 5 COVID social distancing behaviors, 31.5% did not attend any social gatherings, and 40.1% reported feeling lonely. Compared to individuals without a cancer history, individuals with a cancer history were more likely to contact no one outside of the household (49.0% vs. 41.9%, p &lt; 0.01) and less likely to report feeling lonely (35.8% vs. 45.3%, p &lt; 0.01). Among individuals with a cancer history, compared to their counterparts, those who were older, Black, Asian, and living in metro counties were adherent to more social distancing behaviors (mean differences = 0.02, 0.62, 0.71, 0.13, respectively, p all &lt; 0.05) and attended fewer social gathering (mean differences = -0.01, -0.29, -0.49, -0.12, respectively, p all &lt; 0.05). Higher adherence to social distancing behaviors was associated with higher odds of loneliness among individuals with (OR = 1.27, 95% CI: 1.72-1.38) and without a cancer history (OR = 1.15, 95% CI: 1.06-1.25). Conclusions: Social distancing practices and loneliness during the COVID-19 pandemic varied between individuals with and without a cancer history. These findings can inform efforts to support and address all aspects of health among individuals susceptible to loneliness during the pandemic, especially those with a history of cancer.
Analysis of the contribution of macrophages to the overall tumor PD-L1 microenvironment using a screening multi-tumor tissue microarray and rapid multiplex fluorescence digital phenotyping approach.
Authors: Marie Cumberbatch, Douglas Wood, Gourab Chatterjee, Christopher Womack, Milan Bhagat, Lorcan Sherry
Journal: Journal of Clinical Oncology (2022)

2620 Background: Programmed death ligand-1 (PD-L1) contributes to immune suppression in the tumor microenvironment (TME) by interacting with programmed cell death-1 (PD-1) on infiltrating T lymphocytes leading to tumor immune escape. Application of omics technologies has shed light on the relevance of the TME for response to immunotherapies and development of novel treatment options. Here we have applied a multi-plex immunofluorescence/multi-tumor tissue microarray (TMA) approach to examine the immunobiology of different TMEs with respect to the contribution by tumor cells and macrophages to overall PD-L1 expression. Methods: A TMA comprising 11 tumor types and a total of 144 different donors, each represented by two cores [1mm; 1 from invasive margin (IM) and 1 from tumor center (TC)], was stained using Ultivue’s Immuno8 FixVUE panel (CD3, CD4, CD8, FOXP3, CD68, PD-1, PD-L1, pan-CK/SOX10). Whole slide images from two rounds of imaging (x20 magnification; four markers in each round) were aligned using Ultivue's UltiStacker software based on the nuclear counterstains from the two imaging rounds, to provide precise marker colocalization data. Cell phenotype data for each core was generated using Visiopharm software. Results: Overall PD-L1 positivity was greatest for NSCLC, SCLC, TNBC and gastric cancer ranging from approximately 600-1000 PD-L1+ cells/mm 2 /core, compared with CRC, breast, pancreatic, liver, and gastric esophageal junction (GOJ) cancers (approx. 50-300 PD-L1+ cells/mm 2 /core). Contribution by macrophages to overall PD-L1 expression (dual CD68+/PD-L1+) varied by tumor type representing 25-35% for NSCLC (SCC and ADC) and gastric cancer, whereas a converse pattern was apparent for SCLC, TNBC, breast (ER+ and Her2+) and pancreatic cancers where PD-L1+ macrophages accounted for a large proportion (approx. 60-85%) of overall tumor PD-L1 expression. Interestingly, as a proportion of total macrophage infiltration, approximately 65% of CD68+ macrophages were PD-L1+ for SCLC and TNBC, compared with less than 10% for pancreatic and liver cancer. Spatial analysis revealed PD-L1+ macrophage infiltration to be generally higher for IM versus TC, and the distribution between tumor (CK+) and stroma (CK-) remained similar despite exclusion of CD3+/CD8+ cytotoxic T cells from CK+ tumor regions for pancreatic and liver cancer. Conclusions: Taken together, these data illustrate the benefits of combining multiplexed immunofluorescence staining, with digital analysis of cell phenotypes within well characterized tumor samples to better understand the relative immunobiology of different TMEs. Here we demonstrate that the relative contribution of macrophages to the overall PD-L1 microenvironment varies between tumor types, which may help guide options for successful immunotherapy strategies.
Neutrophil-to-lymphocyte ratio as a predictor of survival in head and neck squamous cell carcinoma patients treated with cisplatin.
Authors: Derek Kao, Rocco Ferrandino, Scott Roof, Keith Magnus Sigel
Journal: Journal of Clinical Oncology (2022)

e18004 Background: Neutrophil-to-lymphocyte ratio (NLR) is an easily attainable biomarker that is correlated with systemic inflammation and identifies increased risk of treatment complications and decreased survival in patients with cancer. Our objective was to investigate the use of NLR as an independent prognostic predictor of survival in patients with head and neck squamous cell carcinoma (HNSCC) treated with cisplatin chemotherapy. Methods: We conducted a retrospective study of 2,084 patients in the Veterans Health Affairs system with stages III–IVB head and neck squamous cell carcinoma diagnosed between 2000–2014 and treated with cisplatin-based chemoradiotherapy for curative intent. We calculated NLR values from laboratory values collected in the 30 days prior to initiation of chemoradiotherapy and dichotomized NLR using the Youden J-statistic (NLR = 3.64). We then compared outcomes using Cox proportional hazards methods, adjusting for sociodemographic characteristics (age, race, and sex), date of cancer diagnosis, smoking status, alcohol use, primary site of tumor, tumor characteristics (overall stage, T stage, and N stage), comorbidity score, eGFR, baseline neuropathy and hearing loss, BMI, and oncologic surgical procedures. Results: The cohort had a median age of 61. 99% of cases were male, 82% were white, 13% were black, and 4% were Hispanic. 36% of cases had an NLR &gt; 3.64 prior to treatment initiation. Median overall survival was 32.6 months for the low-NLR group and 24.9 months for the high-NLR group. In unadjusted analyses, a high NLR was associated with an increased risk of all-cause death (hazard ratio [HR]: 1.21; 95% CI 1.08–1.34). In adjusted analyses, high NLR retained significance and predicted overall survival (HR: 1.15; 95% CI 1.02–1.30). We also performed a secondary analysis for death within six months of cancer diagnosis; high NLR was associated with &gt; 50% increased risk of death after adjustment (HR: 1.56; 95% CI 1.04–2.33). Conclusions: In this large cohort of Veterans with advanced HNSCC undergoing chemoradiotherapy, NLR was an independent prognostic predictor of survival. NLR may be a useful clinical risk stratification tool prior to chemoradiotherapy initiation.
Natural language processing of Veterans’ electronic health records to confirm diagnoses of monoclonal gammopathy of undetermined significance.
Authors: Mei Wang, Yao-Chi Yu, Lawrence Liu, Martin W. Schoen, Theodore Seth Thomas, Graham A. Colditz, Su-Hsin Chang
Journal: Journal of Clinical Oncology (2022)

1557 Background: The Veterans Health Administration (VHA) provides extensive electronic health records (EHRs) on Veterans nationwide. Our prior studies utilized VHA data to study the risk of progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma. These studies relied on International Classification of Disease (ICD) codes and manual abstraction on clinical notes to both identify and verify MGUS patients. Diagnosis confirmation is necessary because many providers place a diagnosis on the clinical notes to order lab tests, which is often left in the EHR despite a negative test result. However, manual abstraction is labor intensive and time consuming. With the advancement in natural language processing (NLP), we developed a model to make MGUS confirmation more efficient. Methods: We randomly selected 700 patients within patients diagnosed with MGUS from 1999-2021 in the VHA identified via ICD codes. A random sample of 500 patients were selected and split into the training (80%) and the testing (20%) sets. The remainder (n = 200) served as the validation set. There were 32,708 unstructured hematology/oncology Text Integration Utility reports and 9,237 lab reports (including 2,322 discrete results and 6,915 unstructured comments). All reports were manually reviewed to confirm MGUS diagnoses and served as the reference standard. We compiled three lists of keywords suggestive of MGUS diagnosis, subtypes of immunoglobulins, and negation modifiers. We trained a symbolic NLP model to identify diagnoses using combinations of the lists along with M-protein levels from lab reports. The optimized combination that gave the highest recall and precision from the training set was used and evaluated on the testing and validation sets. Results: Among patients with ICD codes for MGUS, manual abstraction confirmed 84% MGUS diagnoses in the testing set and 80% in the validation set. Our NLP model in the training set confirmed 75% and achieved recall, precision, accuracy, and F1 score of 88.1, 98.7, 89.0, and 93.1%, respectively; in the validation set, our rule confirmed 76% patients and the recall, precision, accuracy, and F1 score were 89.4, 94.7, 87.5, and 92.0%, respectively. On average data abstraction took five minutes per patient (excluding data loading time), whereas NLP model completed 13 patients per minute. Conclusions: The developed NLP model to confirm MGUS diagnosis improves accuracy in diagnosis, compared to ICD codes alone. While the performance is similar to that of manual abstraction, our NLP model is an efficient and viable method in MGUS diagnosis confirmation. [Table: see text]